About the Role
You will lead team recruitment, training, performance management, and echelon building, establishing technical standards and work norms to build a high-efficiency collaborative data team. You will plan and build core data infrastructure including data warehouse, data lake, and real-time data platform, designing business-adaptive data models and layered architectures to unify integration of multi-source data such as trading, payment, user, and operation data. You will build and implement enterprise-level data governance systems covering data quality, security, caliber, and lifecycle management to eliminate data silos and ensure data accuracy, integrity, and reusability. You will lead the selection, construction, and optimization of data platforms and tools such as Databricks, AWS, Spark, and Kafka, promoting big data and cloud native best practices to improve data development efficiency. You will connect deeply with cross-departmental business needs across trading, payment, compliance, and operations, providing customized data analysis, dashboards, and API support to empower data-driven business growth and risk control. You will oversee the whole lifecycle of key data projects including platform upgrades, data integration, and governance implementation, controlling project progress, quality, and cost to ensure on-time delivery. You will track the latest trends in big data, data governance, and cloud technologies, introducing industry best practices to continuously optimize the company's data system.
Requirements
- Bachelor's/Master's degree in Computer Science, Software Engineering, Data Science or related fields
- 8+ years of data industry experience, 3+ years of data team management experience; crypto/fintech/payments industry experience is a MUST
- Proficiency in big data tech stack: Apache Spark/Flink/Kafka (real-time/offline data processing), Databricks/Delta Lake
- Hands-on experience in data warehouse/lake architecture design and implementation
- Expertise in AWS cloud services (EC2, S3, Glue, EMR, Redshift)
- Mastery of data modeling methodologies (dimensional modeling, star/snowflake schema); rich experience in financial/trading data modeling
- Solid programming skills in Python/Scala/Java; proficient in ETL development process
- Proven experience in building and implementing enterprise-level data governance systems
- Excellent team leadership and project management capabilities; strong business acumen
- Outstanding cross-departmental communication and collaboration skills
- Fluent in English (written & spoken)
Responsibilities
- Lead team recruitment, training, performance management and echelon building; establish technical standards and work norms to build a high-efficiency collaborative data team
- Plan and build core data infrastructure (data warehouse, data lake, real-time data platform) and design business-adaptive data models/layered architectures for unified integration of multi-source data
- Build and implement enterprise-level data governance systems (data quality, security, caliber, lifecycle management) to eliminate data silos and ensure data accuracy, integrity and reusability
- Lead the selection, construction and optimization of data platforms/tools (Databricks, AWS, Spark, Kafka, etc.); promote best practices of big data and cloud native technologies
- Connect with cross-departmental business needs (trading, payment, compliance, operation); provide customized data analysis, dashboards and API support
- Oversee the whole lifecycle of key data projects (platform upgrade, data integration, governance implementation); control project progress, quality and cost
- Track the latest trends in big data, data governance and cloud technologies; introduce industry best practices